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Prof. Dr.-Ing. habil. Andreas Mitschele-Thiel

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Thema

SON Self-Coordination Framework using Restricted Boltzmann Machines based Recommender Systems

Typ:
Studienarbeit, Advanced Research Project (MSCSP)
Betreuer:
M.Sc. Tanmoy Bag
Status:
ausgeschrieben
Beschreibung:
Restricted Boltzmann Machine (RBM) based Recommender System (RecSys) is to be studied and implemented to learn its applicability in the domain of Self-Organizing Network functions (SFs). The objective is to model the dynamics between the concurrently executing SFs in order to recommend appropriate network configurations according to the changing state of the environment.

Tasks
- Literature study on the conflict between ICIC and CCO SFs.
- Literature study on Deep Learning based Restricted Boltzmann Machines and Recommender Systems.
- Implement RBM based RecSys with the available infrastructure and compare results with state-of-the-art approaches.

Requirements
- Programming experience in Python & C++
- Basic knowledge of Machine Learning algorithms and frameworks

References
1. T. Bag, S. Garg, D. F. Preciado Rojas, A. Mitschele-Thiel, “Machine Learning based Recommender Systems to achieve Self-Coordination between SON Functions”, in IEEE Transactions on Network and Service Management, Accepted Sept. 01, 2020.
2. H. Ben Yedder, U. Zakia, A. Ahmed and L. Trajković, "Modeling prediction in recommender systems using restricted boltzmann machine," 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Banff, AB, 2017, pp. 2063-2068, doi: 10.1109/SMC.2017.8122923.

Thema

Synthetic Data Generation for enhancing Network Data Analytics in Self-Organizing Networks

Typ:
Studienarbeit, Advanced Research Project (MSCSP)
Betreuer:
M.Sc. Tanmoy Bag
Status:
ausgeschrieben
Beschreibung:
Self-Organizing Networks (SON) driven by Artificial Intelligence demand a large amount of data to learn the state of the environment and determine the most suitable configuration parameters accordingly. In real networks, it is a challenge to collect a significant amount of rich and consistent network data that is sufficient for training complex ML models, representing the dynamics between several concurrently executing SON functions (SFs). The idea is to apply Deep Learning techniques to generate relevant synthetic network data that can complement a limited real existing dataset.

Tasks
- Understand the jointly implemented SFs and the corresponding involved variables in the dataset.
- Explore synthetic data generation approaches and implement a suitable one for the given dataset.
- Measure the quality of the generated synthetic network data and the accuracy enhancements it brings to the jointly modeled SON algorithms.

Requirements
- Programming experience in Python
- Basic knowledge of Machine Learning algorithms and frameworks

References
1. T. Zhang, K. Zhu and D. Niyato, "A Generative Adversarial Learning-Based Approach for Cell Outage Detection in Self-Organizing Cellular Networks," in IEEE Wireless Communications Letters, vol. 9, no. 2, pp. 171-174, Feb. 2020, doi: 10.1109/LWC.2019.2947041.
2. B. Hughes, S. Bothe, H. Farooq and A. Imran, "Generative Adversarial Learning for Machine Learning empowered Self Organizing 5G Networks," 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, 2019, pp. 282-286, doi: 10.1109/ICCNC.2019.8685527.

Thema

Research on QoS strategies for MCPTT applications over LTE

Status:
ausgeschrieben
Beschreibung:
The development of Mission Criticial Push To Talk (MCPTT) application over LTE requires the LTE infrastructure to meet the requirements of public safety mission criticial voice communication. This needs QoS strategies to be targeted specifically for MCPTT applications on both RAN (Radio Access Network) and the core network for higher reliability and lower latency.

Tasks:
- Understanding the LTE infrastructure with added modules of IMS, PCRF and VoLTE required for MCPTT functionality
- Research on state of the art QoS strategies on RAN as well as the Core Network
- Propose a QoS scheme with a focus on meeting the latency and reliability requirements of MCPTT application

Thema

Development of delay tolerant routing protocols for android based devices

Typ:
Studienarbeit, Projektseminar, Bachelorarbeit, Advanced Research Project (MSCSP)
Betreuer:
M.Sc. Mehdi Harounabadi
Status:
ausgeschrieben
Beschreibung:
Delay tolerant networks are intermittently connected networks where nodes apply the store-carry-forward mechanism to communicate. This mechanism relies on the mobility of wireless nodes and the forwarding of messages. However, messages must tolerate a long latency due to disconnections in a network. Regarding to the message forwarding in delay tolerant networks, different approaches may be applied such as epidemic, social tie based and history based message forwarding. The goal of this project is to develop an application for the Android platform to emulate the delay tolerant routing protocols.
Tasks:
- The store-carry and forwarding mechanism must be implemented for the android based devices.
- Different forwarding strategies must be compared. The student must test the implemented solution under different scenarios and analyze the results.

Requirement:
Programming for Android devices
Data base
Basics of communication networks

Thema

Modeling a Mobility-Controlled Wireless Node in a Network Simulator

Typ:
Advanced Research Project (MSCSP)
Betreuer:
M.Sc. Mehdi Harounabadi
Status:
ausgeschrieben
Beschreibung:
A mobility-controlled node can leverage a new degree of freedom in wireless networks which is the trajectory planning for the node. The objective of this project is to implement a new mobility model for wireless nodes which can be controlled by an application in a network simulator.
Tasks:
- Implementing a new mobility model in a networks simulator (ONE, NS, OMNet++)
- Study on the impact of controlling mobility in wireless networks

Thema

Real time scheduling algorithm for 5G cellular communication on software defined radios

Typ:
Studienarbeit, Bachelorarbeit, Masterarbeit, Advanced Research Project (MSCSP)
Betreuer:
Zubair Shaik
Status:
ausgeschrieben
Beschreibung:
bitte siehe English Beschreibung.

Thema

Research of the available scheduling algorithms on a setup of NS3 and NI's Labview LTE Application framework using SDRs

Typ:
Studienarbeit, Hauptseminar, Bachelorarbeit, Advanced Research Project (MSCSP)
Betreuer:
Zubair Shaik
Status:
ausgeschrieben
Beschreibung:
bitte siehe English Beschreibung.

Thema

Mission Critical Push To Talk (MCPTT) on LTE Network using SDRs

Typ:
Studienarbeit, Bachelorarbeit, Advanced Research Project (MSCSP)
Betreuer:
Zubair Shaik
Status:
ausgeschrieben
Beschreibung:
bitte siehe English Beschreibung.

Thema

Mode selection of D2I and D2D communication on LTE/5G

Typ:
Studienarbeit, Bachelorarbeit, Advanced Research Project (MSCSP)
Betreuer:
Zubair Shaik
Status:
ausgeschrieben
Beschreibung:
bitte siehe English Beschreibung.

Thema

D2D Communication on Software Defined Radios (SDRs) for 5G Cellular Networks

Typ:
Studienarbeit, Advanced Research Project (MSCSP)
Betreuer:
Zubair Shaik
Status:
ausgeschrieben
Beschreibung:
bitte siehe English Beschreibung.

Thema

Wireless mesh network of mobile eNBs for LTE backhaul communication

Typ:
Studienarbeit, Bachelorarbeit, Masterarbeit, Advanced Research Project (MSCSP)
Betreuer:
Zubair Shaik
Status:
ausgeschrieben
Beschreibung:
bitte siehe English Beschreibung.

Thema

Novel Dynamic Path Planning Algorithm for localization of wireless nodes in multi-UAV scenario using implicit signaling in DTN

Typ:
Masterarbeit
Betreuer:
M.Sc. Mehdi Harounabadi
M. Sc. Alina Rubina
Status:
ausgeschrieben
Beschreibung:
In unknown environments, dynamic trajectory planning for a UAV represents an effective solution for localizing wireless nodes. The UAV must localize wireless nodes accurately and efficiently without wasting resources.
However, employing a single UAV for localization in vast areas causes long latency and may not be feasible. To overcome these problems, multiple UAVs can be applied in the network.
In this case, cooperation between UAVs is required to avoid redundant visits of already localized nodes. Also, covering the same area by different UAVs will waste time and time is the most crucial parameter in disaster scenarios.
As UAVs may not be always connected to exchange information about their planned trajectory and localized nodes, one possible solution will be employing a signaling of control information among UAVs.
There are two types of signaling. In the first case an explicit signaling is used, where a UAV exchanges the control information whenever it encounters another UAV. However, in the vast networks this cannot be applicable as UAVs have short communication range.
The other feasible solution is implicit signaling through wireless nodes. This can also be called delay tolerant signaling. To implement this, a list of localized nodes is stored in the network among localized nodes.
Wireless nodes act as relay nodes to exchange signaling information among UAVs (indirect signaling of UAVs).
By indirect signaling of UAVs through nodes, the redundancy in time, covered area and number of localized nodes can be decreased significantly. It can improve the latency of localization and decrease the traveled distance of UAVs.
Tasks of the student:
1- Literature review about existing work in static and dynamic UAV trajectory planning for localization and delay tolerant networks routing
2- Developing a cooperative multi-UAV dynamic trajectory planning approach for localization of wireless nodes employing indirect signaling among UAVs
a. Modeling the problem
b. Proposing a solution for the modeled problem
3-Implementation and evaluation of the proposed algorithm comparing two scenarios: no signaling and indirect signaling

Thema

Implementation and Evaluation of Different Path Planning Algorithms for UAV in Wireless Networks

Typ:
Masterarbeit
Betreuer:
M. Sc. Alina Rubina
Status:
ausgeschrieben
Beschreibung:
Quite recently, considerable attention has been paid to the problem of anchor placement, i.e. a design of a trajectory for a mobile anchor (UAV in our case). Previous studies on this issue have shown that a well-planned mobile anchor trajectory increases the speed and accuracy of the localization process [1].
In this paper, one very challenging scenario is considered where an unmanned aerial vehicle (UAV) is flying over an urban area, which suffers from a disaster. The purpose of a UAV is to localize ’survived’ devices, enabled with Wi-Fi module. The obtained information will help to accelerate the rescue process of people who are stuck inside a building.
This work will be mainly divided into two parts:
1) Simulation part
Implementation of chosen three trajectories (namely, Sierpiński curve, Lebesgue curve and Peano curve) in Python.
Simulation of those and comparison with the existing trajectories.
Consideration of two scenarios, with and without a building.
Based on the simulation results, choosing one or two for the experimental evaluation.
2) Experimental part
Evaluation of the chosen trajectory in a real-world experiment considering two scenarios.

Thema

Applying the solution of the vehicle routing problem for path planning of multiple message ferries

Typ:
Diplomarbeit, Projektseminar, Masterarbeit
Betreuer:
M.Sc. Mehdi Harounabadi
Status:
ausgeschrieben
Beschreibung:
Message ferrying is a solution to exchange delay tolerant messages among disconnected wireless nodes that are located out of the transmission range of each other. A ferry node (e.g. UAV), travels among disconnected nodes and deliver their messages. The mobility of a ferry node can be controlled and its travel path can be given in advance. Vehicle routing problem (VRP) is a combinatorial optimization problem which defines set of optimal routes for a fleet of vehicles.
The goal of this project is to model the message ferry path planning problem as VRP and to propose a solution to minimize the message delivery delay in a message ferry network.

Thema

Recommender System with Deep Learning based AutoEncoder for coordinating SON Functions online

Typ:
Advanced Research Project (MSCSP)
Betreuer:
M.Sc. Sharva Garg
Status:
in Bearbeitung
Beschreibung:
Edge network data analytics can support the complex modelling of the complementing and conflicting interactions between the diverse SON functions in a data-driven manner. In this project, Autoencoder based Recommender System is to be implemented as a cloud solution that can recommend SON configurable parameters online, according to the changing state of the mobile network.

Tasks
- Literature study on Autoencoder based Recommender Systems
- Understand 5G service based architecture with a focus on Network Data Analytics Function (NWDAF).
- Implement Autoencoder based RecSys as a service for SONs.

References
1. T. Bag, S. Garg, D. F. Preciado Rojas, A. Mitschele-Thiel, “Machine Learning based Recommender Systems to achieve Self-Coordination between SON Functions”, in IEEE Transactions on Network and Service Management, Accepted Sept. 01, 2020.
2. Yao Wu, Christopher DuBois, Alice X. Zheng, and Martin Ester. 2016. Collaborative Denoising Auto-Encoders for Top-N Recommender Systems. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining (WSDM ’16). Association for Computing Machinery, New York, NY, USA, 153–162.
3. Florian Strub, Jérémie Mary. Collaborative Filtering with Stacked Denoising AutoEncoders and Sparse Inputs. NIPS Workshop on Machine Learning for eCommerce, Dec 2015, Montreal, Canada.

Thema

Offline-online decison making for multi-ferry networks

Typ:
Diplomarbeit, Masterarbeit
Betreuer:
M.Sc. Mehdi Harounabadi
Status:
in Bearbeitung
Beschreibung:
Message ferry networks are disconnected wireless networks where message ferry nodes are employed to travel among disconnected nodes and deliver their messages. The travel path of ferries can be planned offline or ferries can decide their mobility online (on-the-fly). The goal of this project is to propose a message ferry network with multiple message ferries where the path for some ferries are planned offline and other ferries make decision on-the-fly. Each ferry may visit all nodes or a subset of nodes. The assignment of ferries to nodes and type of decision making for a ferry(offline or online) must be done in such a way which the average delay for message delivery in a network is minimized.
The optimization problem should be solved (approximated applying heuristic methods) and the proposed solution must be compared to the networks with pure offline path planning for ferries and networks with pure on-the-fly decision making.
Requirements:
- Understanding of heuristic methods
- Python

Thema

Implementation of localization software for UAV in real-time

Betreuer:
M. Sc. Alina Rubina
Status:
in Bearbeitung
Beschreibung:
In this project we are considering mobile anchor based localization. We are using an UAV as a mobile anchor and mobile phones represent wireless sensors. UAV explors the area and measures received signal strength of mobile phones which need to be localized. Localization process includes mapping those received signal strengths to distances. Also, knowing the distances we can estimate the position of the node.
The main goal of this project is to develop a localization software for UAV. This software needs to process data in real-time.

Thema

Performance evaluation of different multi-ferry path planning approaches

Typ:
Masterarbeit
Betreuer:
M.Sc. Mehdi Harounabadi
Status:
in Bearbeitung
Beschreibung:
Message ferrying is a solution to exchange delay tolerant messages among distant wireless nodes that are located out of the transmission range of each other. The ferry node (UAV), flies to visit ground nodes and in each contact exchange information with them. Ferry is a wireless node with controllable mobility. It picks up messages from a ground node, flies to the destination and offloads messages. Decision about which ground node to visit (ferry path planning) impacts the performance of message forwarding in network. Having a single ferry in networks that has been established in large areas cannot support communication needs of different traffic types in the network. Multi-ferry approach employs several ferries in the network to meet the performance requirements of the network. Several approaches has been proposed in literature for multi ferry path planning. The objective of this project is:
1. Literature study on existing multi ferry path planning approaches
2. Implementation of some of the selected multi ferry approaches on the existing simulator (python based simulator)
3. Investigation on results to make conclusion

Thema

Survey: Aerial Base Station Placement in Future Cellular Networks

Typ:
Hauptseminar
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Model-Based Prediction of the Aerial Base Station Position Based on Local Information

Typ:
Hauptseminar
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Drone-Aided Communication as a Key Enabler for 5G and Resilient Public Safety Networks

Typ:
Hauptseminar
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Implementierung eines Computerspiels auf Basis eines Luftbasisstationssimulators

Typ:
Studienarbeit, Hauptseminar
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Particle Swarm Optimization for Aerial Base Station Placement

Typ:
Bachelorarbeit
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Air-to-ground Propagation Model Parameter Estimation

Typ:
Masterarbeit
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Implementation of Resource Scheduling Algorithms for LTE Radio Systems in Python-based Simulation Environment

Typ:
Bachelorarbeit
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Implementation and Performance Evaluation of Multiple Reuse in Overlay D2D Communication

Typ:
Advanced Research Project (MSCSP)
Betreuer:
M.Sc. Dariush M. Soleymani
Status:
abgeschlossen
Abstract:

Thema

Spectrum Sharing Algorithms for D2D Communication in Cellular Networks

Typ:
Diplomarbeit, Hauptseminar, Masterarbeit, Advanced Research Project (MSCSP)
Betreuer:
M. Sc. Abubaker Matovu Waswa
Status:
abgeschlossen
Abstract:

Thema

Fair Radio Resource Allocation Algorithms for D2D Communication Underlaying Cellular Networks

Betreuer:
M. Sc. Abubaker Matovu Waswa
Status:
abgeschlossen
Abstract:

Thema

Survey on Resource Scheduling Mechanisms in LTE Systems

Typ:
Studienarbeit, Hauptseminar
Betreuer:
Dr.-Ing. Oleksandr Andryeyev
Status:
abgeschlossen
Abstract:

Thema

Überblick über Techniken zur dynamischen Frequenzzuteilung in der drahtlosen Kommunikation der Zukunft

Typ:
Hauptseminar
Betreuer:
M.Sc. Dariush M. Soleymani
Status:
abgeschlossen
Abstract: